Solving multiple linear regression problem using artificial neural network

<span>Multiple linear regressions are an important tool used to find the relationship between a set of variables used in various scientific experiments. In this article we are going to introduce a simple method of solving a multiple rectilinear regressions (MLR) problem that uses an artificial neural network to find the accurate and expected output from MLR problem. Different artificial neural network (ANN) types with different architecture will be tested, the error between the target outputs and the calculated ANN outputs will be investigated. A recommendation of using a certain type of ANN based on the experimental results will be raised.</span>

Strengthening Quality of Chaotic Bit Sequences

We discuss chaos and its quality as measured through the 0-1 test for chaos. When the 0-1 test indicates deteriorating quality of chaos, because of the finite precision representations of real numbers in digital implementations, then the process may eventually lead to a periodic sequence. A simple method for improving the quality of a chaotic signal is to mix the signal with another signal by using the XOR operation. In this paper, such mixing of weak chaotic signals is considered, yielding new signals with improved quality (with K values from the 0-1 test close to 1). In some sense, such a mixing of signals could be considered as a two-layer prevention strategy to maintain chaos. That fact may be important in those applications when the hardware resources are limited. The 0-1 test is used to show the improved chaotic behavior in the case when a continuous signal (for example, from the Chua, Rössler or Lorenz system) intermingles with a discrete signal (for example, from the logistic, Tinkerbell or Henon map). The analysis is presented for chaotic bit sequences. Our approach can further lead to hardware applications, and possibly, to improvements in the design of chaotic bit generators. Several illustrative examples are included.

Easy Fabrication of Performant SWCNT-Si Photodetector

We propose a simple method to fabricate a photodetector based on the carbon nanotube/silicon nitride/silicon (CNT/Si3N4/Si) heterojunction. The device is obtained by depositing a freestanding single-wall carbon nanotube (SWCNT) film on a silicon substrate using a dry transfer technique. The SWCNT/Si3N4/Si heterojunction is formed without the thermal stress of chemical vapor deposition used for the growth of CNTs in other approaches. The CNT film works as a transparent charge collecting electrode and guarantees a uniform photocurrent across the sensitive area of the device. The obtained photodetector shows a great photocurrent that increases linearly with the incident light intensity and grows with the increasing wavelength in the visible range. The external quantum efficiency is independent of the light intensity and increases with the wavelength, reaching 65% at 640 nm.

PtNi Alloy Coated in Porous Nitrogen-Doped Carbon as Highly Efficient Catalysts for Hydrogen Evolution Reactions

The development of low platinum loading hydrogen evolution reaction (HER) catalysts with high activity and stability is of great significance to the practical application of hydrogen energy. This paper reports a simple method to synthesize a highly efficient HER catalyst through coating a highly dispersed PtNi alloy on porous nitrogen-doped carbon (MNC) derived from the zeolite imidazolate skeleton. The catalyst is characterized and analyzed by physical characterization methods, such as XRD, SEM, TEM, BET, XPS, and LSV, EIS, it, v-t, etc. The optimized sample exhibits an overpotential of only 26 mV at a current density of 10 mA cm−2, outperforming commercial 20 wt% Pt/C (33 mV). The synthesized catalyst shows a relatively fast HER kinetics as evidenced by the small Tafel slope of 21.5 mV dec−1 due to the small charge transfer resistance, the alloying effect between Pt and Ni, and the interaction between PtNi alloy and carrier.

Simple method for making MWCNTs/Au-NPs-based biosensor electrodes

Multiwalled carbon nanotubes have great potential when applied as biosensors. Their properties, especially as electrodes with electrochemical characteristics, offer strong benefits for developing biosensors. This research has been able to integrate multiwalled carbon nanotubes (MWCNTs) with Au nanoparticles (Au-NPs) to obtain several new superior properties. Cysteaminium chloride is used to link MWCNTs and Au-NPs while binding to specific antibodies to make them more sensitive to some diseases or viruses. The data on the success of the bonding of MWCNTs/Au-NPs were tested using three characterizations, namely FTIR, SEM, and XRD. Based on the results of testing electrochemical properties using the CV and EIS tests, the capacitance value of 6,363 Fg-1 and the Rct value of 717,9 Ω, respectively. This demonstrates good adhesion and electron transfer properties from the electrolyte to the probe and electrode.

Underwater Video as a Tool to Quantify Fish Density in Complex Coastal Habitats

Habitat loss is a serious issue threatening biodiversity across the planet, including coastal habitats that support important fish populations. Many coastal areas have been extensively modified by the construction of infrastructure such as ports, seawalls, docks, and armored shorelines. In addition, habitat restoration and enhancement projects often include constructed breakwaters or reefs. Such infrastructure may have incidental or intended habitat values for fish, yet their physical complexity makes quantitatively sampling these habitats with traditional gears challenging. We used a fleet of unbaited underwater video cameras to quantify fish communities across a variety of constructed and natural habitats in Perdido and Pensacola Bays in the central northern Gulf of Mexico. Between 2019 and 2021, we collected almost 350 replicate 10 min point census videos from rock jetty, seawall, commercial, public, and private docks, artificial reef, restored oyster reef, seagrass, and shallow sandy habitats. We extracted standard metrics of Frequency of Occurrence and MaxN, as well as more recently developed MeanCount for each taxon observed. Using a simple method to measure the visibility range at each sampling site, we calculated the area of the field of view to convert MeanCount to density estimates. Our data revealed abundant fish assemblages on constructed habitats, dominated by important fisheries species, including grey snapper Lutjanus griseus and sheepshead Archosargus probatocephalus. Our analyses suggest that density estimates may be obtained for larger fisheries species under suitable conditions. Although video is limited in more turbid estuarine areas, where conditions allow, it offers a tool to quantify fish communities in structurally complex habitats inaccessible to other quantitative gears.

Quantum Fourier transform to estimate drive cycles

Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for control applications related to fuel efficiency, emission reduction and improving safety. Quantum computing has established the computational efficiency that can be gained. A drive cycle frequency estimation algorithm based on the quantum Fourier transform is exponentially faster than the classical Fourier transform. The algorithm is applied on real world data set. We evaluate the method using a quantum computing simulator, demonstrating remarkable consistency with the results from the classical Fourier transform. Current quantum computers are noisy, a simple method is proposed to mitigate the impact of the noise. The method is evaluated on a 15 qubit IBM-q quantum computer. The proposed method for a noisy quantum computer is still faster than the classical Fourier transform.

Green and Affordable Manufacturing Method for Multi-Scale Porous Carbon Nanofibers and Its Application in Vanadium Redox Flow Battery

Carbon nanofibers with multi-scale pores have been easily constructed by synchronous water etching during the carbonization process of PAN nanofibers, reducing the additional consumption of energy and time. After etching by high-temperature water vapor, the fiber surface becomes more coarse, and large amounts of etched pits are formed, effectively increasing the electrode’s specific surface area and hydrophilicity. Oxygen content is also significantly increased, which may effectively increase the electrocatalytic active sites of the electrode. Electrochemical tests verified the improved electrocatalytic activity and increased effective surface area. As a result, the VRFB single cell with water vapor etched carbon nanofibers as its electrode shows higher battery efficiencies than that with pristine carbon nanofibers; the energy efficiency improves by nearly 9.4% at 200 mA·cm-2. After 100 charge/discharge cycles, the battery efficiency has no obvious attenuation, and the capacity attenuation rate of single cycle is nearly 0.26%，suggesting a satisfactory cycling stability. This green and simple method for constructing multi-scale porous carbon nanofibers electrode is expected to achieve large-scale production of high-performance electrode materials, and can be applied in various electrochemical energy storage systems.

Prediction of southern oscillation index using spectral components

The time series of SOI (Southern Oscillation Index, Tahiti minus Darwin sea-level atmospheric pressure difference) was spectrally analysed by a simple method MEM-MRA, where periodicities are detected by MEM (Maximum Entropy Method) and used in MRA (Multiple Regression Analysis) to get the estimates of their amplitudes and phases. From these, the three or four most prominent ones were used for reconstruction and prediction. Using data for 1935-80 as dependent data, the reconstructed values of SOI matched well with observed values and most of the El Niños (SOI minima) and La Niñas (SOI maxima) were located correctly. But for the independent data (1980 onwards), the matching was poor. Omitting earlier data, 1945- 80, 1955-80, 1965-80 as dependent data again gave poor matching for 1980 onwards. When data for 1980 onwards only were used as dependent data, the matching was better, indicating that the spectral characteristics have changed considerably with time and recent data were more appropriate for further predictions. The 1997 El Niño was reproduced only in data for 1985 onwards. For 1990 onwards, only a single wave of 3.5 years was appropriate and explained the 1997 and 1994 events but only one (1991) of the 3 complex and quick events that occurred during 1989-95. The UCLA group of Dr. Ghil has been using the SSA (Singular Spectrum Analysis)-MEM combination for SOI analysis. For the 1980s, they got very good matching, but the 1989-95 structures were not reproduced. For recent years, their SSA-filtered SOI (used for prediction) is a simple sinusoid of ~3.5 years. It predicted the El Niño of 1997 only at its peak and even after using data up to February 1997, the abrupt commencement of the event in March 1997 and its abrupt end in June 1998 could not be predicted. Using only a 3.5 years wave, an El Niño was expected for 2000-2001. However, a very long-lasting La Niña seems to be operative and there are no indications as yet (September of 2001) of any El Niño like conditions.

Visualization of Escher-like Spiral Patterns in Hyperbolic Space

Spirals, tilings, and hyperbolic geometry are important mathematical topics with outstanding aesthetic elements. Nonetheless, research on their aesthetic visualization is extremely limited. In this paper, we give a simple method for creating Escher-like hyperbolic spiral patterns. To this end, we first present a fast algorithm to construct Euclidean spiral tilings with cyclic symmetry. Then, based on a one-to-one mapping between Euclidean and hyperbolic spaces, we establish two simple approaches for constructing spiral tilings in hyperbolic models. Finally, we use wallpaper templates to render such tilings, which results in the desired Escher-like hyperbolic spiral patterns. The method proposed is able to generate a great variety of visually appealing patterns.